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Published in: Lasers in Medical Science 7/2020

01-09-2020 | Vancomycin | Original Article

Deciphering biophysical signatures for microbiological applications

Authors: Harsh Ranawat, Nirmal Mazumder, Thokur Sreepathy Murali, Krishna Kishore Mahato, Kapaettu Satyamoorthy

Published in: Lasers in Medical Science | Issue 7/2020

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Abstract

Identification and classification of microbes are vital for maintenance of normal and altered state of human health and have applications in pharmaceutical industries, food processing, clinical analysis, and treatment. Development of methods aimed towards achieving these goals must be rapid and reliable. Conventional physiochemical and morphology-based methods of identification are often ambiguous, while newer molecular methods such as flow cytometry and polymerase chain reaction, though reliable, are time and resource intensive. Spectroscopic methods provide advantages over conventional methods as these can be fast, non-destructive, and highly specific. Surface charge of bacteria is an important parameter which can reveal composition of cell wall and is attributed to the presence of carboxyl and phosphoryl groups. Interaction of the cell with the solvent and response to various stresses can hence be measured by the changes in surface charge. In this study, we have obtained auto-fluorescence spectra (tryptophan) and dynamic light scattering (DLS) measurements from common pathogenic strains of Pseudomonas aeruginosa and Staphylococcus aureus. Fluorescence emission spectra were obtained in the range of 300–550 nm at excitation wavelength of 280 nm and DLS measurements comprised zeta potential and size parameters. Both types of measurements were performed in physiological and stress-induced conditions such as heat, sonication, and antibiotic treatment with vancomycin and cetylpyridinium chloride. Effects of these antibiotics on membrane integrity and cell viability, as obtained by DLS measurements, were statistically significant and comparable with conventional methods. Multivariate analysis enabled clustering of 83% of the samples at the genera level, based on variances from auto-fluorescence and DLS measurements.
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Metadata
Title
Deciphering biophysical signatures for microbiological applications
Authors
Harsh Ranawat
Nirmal Mazumder
Thokur Sreepathy Murali
Krishna Kishore Mahato
Kapaettu Satyamoorthy
Publication date
01-09-2020
Publisher
Springer London
Published in
Lasers in Medical Science / Issue 7/2020
Print ISSN: 0268-8921
Electronic ISSN: 1435-604X
DOI
https://doi.org/10.1007/s10103-019-02936-9

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